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06-12-2018 | Computer aided Medical Diagnosis

A new EEG software that supports emotion recognition by using an autonomous approach

Authors: Roberto Munoz, Rodrigo Olivares, Carla Taramasco, Rodolfo Villarroel, Ricardo Soto, María Francisca Alonso-Sánchez, Erick Merino, Victor Hugo C. de Albuquerque

Published in: Neural Computing and Applications | Issue 15/2020

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Abstract

Human behavior is manly addressed by emotions. One of the most accepted models that represent emotions is known as the circumplex model. This model organizes emotions into points on a bidimensional plane: valence and arousal. Despite the importance of the emotion recognition, there are limited initiatives that seek to classify emotions easily in an uncontrolled environment. In this work, we present the architecture and the design of an extensible software which allows recognizing and classifying emotions by using a low-cost EEG. The proposed software implements an emotion classifier although a support vector machines (SVM) are boosted with an autonomous bio-inspired approach. The contribution was experimentally evaluated by taking a set of well-known validated EEG Databases for Emotion Recognition. Computational experiments show promising results. Using our proposal for EEG emotion classification, we reach an accuracy close to 95%. The results obtained confirm that our approach is able to overcome to a commonly used SVM classifier and that the proposed software can be useful in real environments.

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Title: A new EEG software that supports emotion recognition by using an autonomous approach
Authors: Roberto Munoz
Rodrigo Olivares
Carla Taramasco
Rodolfo Villarroel
Ricardo Soto
María Francisca Alonso-Sánchez
Erick Merino
Victor Hugo C. de Albuquerque
Publication date: 06-12-2018
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 15/2020
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-018-3925-z

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